Design and validation of an MPC-based torque blending and wheel slip control strategy

Satzger, Clemens; Castro, Ricardo de; Knoblach, Andreas; Brembeck, Jonathan

doi:10.1109/ivs.2016.7535435

Cited by 15 publications

(10 citation statements)

References 14 publications

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“…A linear MPC strategy is developed in [10], where the ABS slip regulation is achieved through torque blending between the friction brakes and in-wheel motors. Similarly, [11], [12] and the very recent research [13] combine ABS control and torque blending, by using a linear MPC formulation. [14] presents an MPC-based ABS, with test results on a hardware-in-the-loop rig.…”

Section: Introductionmentioning

confidence: 99%

Explicit Nonlinear Model Predictive Control for Electric Vehicle Traction Control

Tavernini

Metzler

Gruber

et al. 2019

IEEE Trans. Contr. Syst. Technol.

103

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Abstract-This study presents a traction control system for electric vehicles with in-wheel motors, based on explicit non-linear model predictive control. The feedback law, available beforehand, is described in detail, together with its variation for different plant conditions. The explicit controller is implemented on a rapid control prototyping unit, which proves the real-time capability of the strategy, with computing times in the order of microseconds. These are significantly lower than the required sampling time for a traction control application. Hence, the explicit model predictive controller can run at the same frequency as a simple traction control system based on Proportional Integral (PI) technology. High-fidelity model simulations provide: i) a performance comparison of the proposed explicit non-linear model predictive controller with a benchmark PI-based traction controller with gain scheduling and anti-windup features; and ii) a performance comparison among two explicit and one implicit non-linear model predictive controllers based on different internal models, with and without consideration of transient tire behavior and load transfers. Experimental test results on an electric vehicle demonstrator are shown for one of the explicit non-linear model predictive controller formulations.Index Terms-traction control, wheel slip, model predictive control, PI control, electric vehicle, in-wheel motors.Sorniotti (email: a.sorniotti@surrey.ac.uk) are with the

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Section: Introductionmentioning

confidence: 99%

Explicit Nonlinear Model Predictive Control for Electric Vehicle Traction Control

Tavernini

Metzler

Gruber

et al. 2019

IEEE Trans. Contr. Syst. Technol.

103

View full text Add to dashboard Cite

show abstract

“…Vários trabalhos têm focado em controle híbrido de freio motor e freio de fricção, como é o caso e Satzger et al (2016), nos quais o controle é feito pela minimização de uma função custo que tem como referência o deslizamento e torque a ser aplicado efetivamente nas rodas. Deslizamento de referência também é utilizado em Chiang et al (2014) 2017) utilizam a medida da desaceleração para criar ciclos de torques de frenagens nos trens de pouso, já sendo observado o uso das medidas de desaceleração para o controle do torque de frenagem na roda.…”

Section: Introdu ç ãOunclassified

Controle Preditivo da Frenagem de um Monociclo em Terreno Desconhecido

Pinto

Ferreira

Meggiolaro

et al. 2021

Procedings Do XV Simpósio Brasileiro De Automação Inteligente

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Braking systems that prevent wheel locking are employed in both land and air vehicles. This work develops a control that avoids the locking of the wheels during braking. For this purpose, a slip control was carried out for the case where there is only the longitudinal movement of the unicycle. The slip, calculated from the states (longitudinal speed of the vehicle and angular speed of the wheel), is compared to a reference slip, which is updated through the feedback of the states and torque. The control uses the Nonlinear Model Predictive Control (NMPC) strategy, considering the system restrictions. Finally, performance cost functions were calculated to validate the results obtained in the control. Resumo: Sistemas de frenagem que evitam o travamento da roda são empregados tanto em veículos terrestres quanto aéreos. Este trabalho desenvolve um controle que evita o travamento das rodas durante uma frenagem em movimento apenas longitudinal de um modelo de monociclo por meio do controle do deslizamento entre a roda e o solo. O deslizamento, calculado por meio dos estados (velocidade longitudinal do veículo e velocidade angular da roda), é comparado a um deslizamento de referência, este sendo atualizado por meio do feedback dos estados e do torque. O controle utiliza a estratégia do Nonlinear Model Predictive Control (NMPC), comportando as restrições do sistema. Por fim, funções de custo de performance foram calculadas para validar os resultados obtidos do controle.

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“…In [16] an ABS based on a gain scheduled linear quadratic regulator was tested on a vehicle with electromechanical brake calipers. Linear MPCs are discussed in [17][18][19], in the context of ABS including torque blending between friction brakes and in-wheel motors. In [20] the MPC strategy is compared with a PI controller, and is assessed on an electric vehicle prototype.…”

Section: Introductionmentioning

confidence: 99%

An Explicit Nonlinear Model Predictive ABS Controller for Electro-Hydraulic Braking Systems

Tavernini

Vacca

Metzler

et al. 2020

IEEE Trans. Ind. Electron.

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This study addresses the development and Hardware-in-the-Loop (HiL) testing of an explicit nonlinear model predictive controller (eNMPC) for an anti-lock braking system (ABS) for passenger cars, actuated through an electro-hydraulic braking (EHB) unit. The control structure includes a compensation strategy to guard against performance degradation due to actuation dead times, identified through experimental tests. The eNMPC is run on an automotive rapid control prototyping unit, which shows its real-time capability with comfortable margin. A validated high-fidelity vehicle simulation model is used for the assessment of the ABS on a HiL rig equipped with the braking system hardware. The eNMPC is tested in 7 emergency braking scenarios, and its performance is benchmarked against a proportional integral derivative (PID) controller. The eNMPC results show: i) the control system robustness with respect to variations of tire-road friction condition and initial vehicle speed; and ii) a consistent and significant improvement of the stopping distance and wheel slip reference tracking, with respect to the vehicle with the PID ABS.

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Design and validation of an MPC-based torque blending and wheel slip control strategy

Cited by 15 publications

References 14 publications

Explicit Nonlinear Model Predictive Control for Electric Vehicle Traction Control

Explicit Nonlinear Model Predictive Control for Electric Vehicle Traction Control

Controle Preditivo da Frenagem de um Monociclo em Terreno Desconhecido

An Explicit Nonlinear Model Predictive ABS Controller for Electro-Hydraulic Braking Systems

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